Analytical Study of Data Mining Applications in Malaria Prediction and Diagnosis

Over the years, healthcare sector has been identified as the most vulnerable sector which is information rich but due to lack of appropriate retrieval methods avail, hidden data pattern cannot be achieved properly. A lot of research persons had already described and identified several research techniques and methods so that information related to various diseases can be viewed, reviewed, predicted and analyzed. In this paper, we have focused to analysis a variety of techniques, approaches and different tools and its impact on the healthcare sector especially for vector borne disease malaria. Malaria fever has been identified as a threat to human existence, killing millions of people annually, and also contributing to economic backwardness due to huge amount of money and time being spent by many countries of the world in managing the menace, mostly Africa and Asia countries. Shortages of medical experts, hospitals, lack of knowledge and necessary equipment have been adjudged some of the prominent factors for the very high number of deaths associated with malaria fever annually. These challenges have made Information Technology (IT) experts to work with medical experts in using modern IT initiatives to address the situation in the form of providing Predictive Models that can carry out diagnosis and in some cases provide therapy. This study looks at some of these Computer Based Systems (Predictive Models) developed to manage malaria with a view to providing meaningful contribution on improving on them. The work looks into present methods and future needs in order to provide computer based viable classifiers in diagnosis and treatment of malaria fever cases. It is hopeful that researchers in the area of providing diagnosis and therapy systems can make use of our valuable improvement suggestions.